From 3M Health Information Systems
Assessing interoperability for MACRA: Our response to the Health & Human Services RFI
Congress has declared a national objective to achieve widespread exchange of electronic health information nationwide by December 31, 2018. By this July, the U.S. Department of Health & Human Services (HHS) must define metrics to determine if (and to what extent) this lofty goal has been met.
HHS recently released a Request for Information (RFI) to stakeholders investigating opportunities and approaches to measuring interoperability. Specifically, the RFI is trying to find the answer to the following questions:
- WHO is the measurement population of interest?
- WHAT components of interoperability should be measured?
- WHICH data sources should be used? and
- HOW are the metrics of interoperability defined?
This blog is a summary of the 3M HIS response to the HHS RFI and includes an answer to one more question: WHY is quantifying interoperability so important?
WHO is the measurement population of interest?
The RFI inquired whether to limit measurement to users with Certified Electronic Health Record Technology (CEHRT) or follow the broader parameters of the Interoperability Road Map. We believe a person-centered learning health system requires that interoperability is realized across the care continuum. If the focus of measurement is limited to “meaningful EHR users,” the ability to gain a person-centered view is limited. Furthermore, if measurement only includes the sector of health care that includes “meaningful EHR users,” it may provide a falsely elevated view of person-centered interoperability. It is important to measure interoperability across the care continuum and stratify and providers as “meaningful EHR users” or not. This introduces the ability to quantify the impact of CEHRT use on interoperability.
WHAT components of interoperability should be measured?
The RFI proposes to measure four aspects of interoperability:
- Electronically sending
- Electronically receiving
- Finding and integrating data from outside sources
- Use of information electronically received from outside sources
We believe that in order to operationalize the broad construct of interoperability, each of these aspects of interoperability (electronic sending, receiving, finding and integrating) must be concretely defined. Most importantly, exchange and use should be quantified. Broad constructs are not specific enough to measure the exchange and utilization of electronic health information. We propose a method to measure interoperability when we answer the ‘WHICH’ and ‘HOW’ questions below.
WHICH data sources should be used?
The common clinical data elements outlined in the Interoperability Roadmap or the standards in the Interoperability Standards Advisory have the level of granularity that is necessary to assess interoperability to improve patient care. However, claims data and reimbursement code sets should be linked to clinical processes and outcomes so that interventions and clinical quality measurement can be linked to cost of care. If the clinical data are not linked with reimbursement code sets there is no direct way to infer that information received in electronic messages contributed to lowering cost and raising value.
HOW are the metrics of interoperability defined?
The RFI suggested collecting survey data to measure interoperability. We agree that it is beneficial to collect and analyze qualitative responses from the survey data. However, survey-based measures are not independently adequate to address the exchange and use of electronic health information. While national surveys are appropriate to gain insight into why electronic health information may not be widely exchanged, they cannot determine causality or quantify interoperability. Additionally, it is critical that the survey be adapted to assess how the exchanged information is being used to impact clinical care.
We believe that it is critical to state and measure compliance with the standards associated with each aspect of interoperability. Existing guidance such as the Interoperability Standards Advisory can be used as a template for assessing the semantics, syntax and services associated with electronic health information exchange. For example, if a provider sends a continuity of care electronic document during a transition of care, it should be in the HL7 Consolidated Clinical Document Architecture (C-CDA) format, and the contents of the document should be compliant with the correct vocabulary standards (such as SNOMED CT for patient problems and RxNorm for medications). Both the structure of the C-CDA and the contents of the C-CDA should be correct (valid and reliable). This is the first step in measuring if the information exchanged can be integrated into a receiving system for subsequent use.
WHY is quantifying interoperability so important?
Interoperability is not the end goal in and of itself. Rather, interoperability is the means to an end with the goal of facilitating high quality and cost efficient care. In the long term, we must measure what interoperability enables. The use of exchanged information should focus on actionable data for improved outcomes and lower healthcare costs. This means that exchanged information cannot be used for reconciliation alone but rather we must measure the use of exchanged information in care decisions and cost management. Some use cases that can quantify the benefits of interoperability include measuring:
- Proportion of received data incorporated into clinical work flow (such as the ability to use received information in clinical decision support notifications)
- Timeliness of information transfer between providers to close the referral loop
- Proportion of exchanged patient allergy information used in drug-drug or drug-allergen checks thus improving medication safety
- Prevention of duplicate tests by incorporating past lab test results and procedures into the receiving electronic system
- Integration of individuals health concerns, preferences or goals to facilitate to improve treatment compliance
Incorporating these measurements is an important process because it contributes to a person-centered longitudinal health record and surfaces exchanged information to be used in care decisions. Quantifying how much of the electronic data was sent using the appropriate standard terminology codes and descriptions is the first step in realizing the benefits of interoperability.
Amy Sheide is a clinical analyst at 3M Health Information Systems and is a member of the Healthcare Data Dictionary (HDD) team.